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This article explains the hardware basis of NUMA, how Linux reads ACPI SRAT and SLIT tables to discover CPU‑memory topology, the kernel functions that initialize NUMA structures, and how the memblock allocator incorporates this information to enable performance‑optimizing tools like numactl.
At Netdev 0x19, ByteDance's STE team presented two talks—one on a NUMA‑locality‑aware MPTCP flow‑selection strategy that can raise throughput by up to 30% and lower tail latency by 6%, and another on a DPDK‑based user‑space MPTCP stack that reduces latency by nearly 10% and more than doubles throughput—showcasing practical performance gains for data‑center networking.
This article explains the fundamentals of NUMA architecture, how Linux detects and represents NUMA nodes, the memory zone hierarchy, allocation policies, and practical techniques such as using numactl and taskset to bind processes for optimal performance on multi‑socket servers.
Virtualization resource scheduling algorithms, especially in OpenStack, address fragmented CPU allocation and uneven node utilization by dynamically consolidating VMs, employing NUMA-aware placement, and using resource scoring to trigger migrations, ultimately improving utilization, reducing costs, and enhancing performance in cloud environments.
Collaborating across TencentOS and database kernel teams, the article details how architecture upgrades—moving to TKE HouseKeeper, switching to AMD CPUs, and adding a portable 16 KB atomic‑write feature—combined with kernel optimizations like huge‑page support, NUMA‑aware qspinlocks, speculative page‑fault handling, and ORC unwinding to deliver up to 30 % mixed workload and over 100 % write‑only performance gains while reducing memory usage.
Koordinator v1.5.0, the 13th major release since its open‑source debut, introduces pod‑level NUMA alignment, Terway network QoS, core scheduling, and numerous performance and stability improvements, while also being accepted as a CNCF Sandbox project and outlining future roadmap plans.
Large folios in the Linux kernel combine multiple pages to reduce TLB misses, page faults, and reclamation cost while enabling more efficient compression; they are supported by filesystems like XFS and bcachefs, and recent patches add multi‑size THP, swap‑in/out handling, TAO allocation, NUMA balancing, and debug tools, with OPPO’s production deployment showing performance gains and motivating broader adoption and fragmentation mitigation.
Katalyst v0.4.0 introduces tidal colocation for mixed workloads, online resource overcommit, fine‑grained NUMA memory management, OOM priority enhancements, and topology‑aware scheduling, providing a comprehensive cost‑optimization solution for cloud‑native Kubernetes clusters.
This article explains DPDK's memory management architecture, covering the hierarchical memory layout, hugepage discovery and mapping, shared configuration structures, NUMA‑aware allocation, custom malloc‑heap implementation, memzone and mempool creation, and the mbuf buffer model, with detailed code examples.
This article explains common Linux memory‑related performance bottlenecks—such as memory reclamation, page‑cache pressure, huge‑page usage, and cross‑NUMA access—and provides practical tuning methods to improve latency and throughput on servers and applications.
This article provides a comprehensive technical overview of DPDK, covering its architecture, core libraries, platform modules, polling and CPU‑affinity techniques, huge‑page memory management, NUMA considerations, OS tuning steps, and integration with OVS for high‑performance packet processing.
This article explains how hardware architecture, Linux OS version, kernel configuration, OVS integration, memory management, NUMA awareness, and CPU micro‑architecture affect DPDK application performance and provides concrete tuning steps such as CPU isolation, service disabling, huge‑page setup, and optimized memory allocation.
This article explains Linux virtual memory concepts, the process of memory allocation, page fault handling, background and direct memory reclamation methods, LRU-based page types, NUMA considerations, tuning parameters like swappiness and min_free_kbytes, and strategies to prevent OOM killer termination.
Evaluating the Cloud Music online estimation system on NUMA‑based servers revealed that CPU pinning across both memory nodes dramatically boosts throughput on high‑end 96‑core machines—up to 75% for complex models—while low‑end servers gain only modestly, confirming NUMA‑aware scheduling’s critical role for CPU‑intensive inference workloads.
The article analyzes the instability of shared‑type virtual machines, introduces enterprise‑level instances with fixed CPU scheduling and NUMA topology, details the applied technologies such as CPU pinning, PCI‑Passthrough and multi‑queue NICs, and presents extensive sysbench and STREAM benchmark results that demonstrate superior isolation, stability and performance of enterprise instances over shared ones.
This article explains how Linux manages physical address space using SMP and NUMA architectures, describes the node, zone, and page data structures, details page allocation via the buddy system and slab allocator, and outlines user‑ and kernel‑mode page‑fault handling, swapping, and address translation mechanisms.
This article explains NUMA architecture, how its memory allocation policies can cause swap‑related performance issues for MySQL, provides step‑by‑step methods to disable NUMA at BIOS, kernel or MySQL levels, and discusses the innodb_numa_interleave parameter and best‑practice recommendations.
This article explains the Linux kernel memory management hierarchy—including NUMA nodes, memory zones, the buddy system for free pages, and the SLAB allocator—providing command‑line examples, code snippets, and visual diagrams to illustrate how the kernel efficiently allocates and reclaims memory.
This article explains the core principles of DPDK memory management, covering standard huge pages, NUMA node binding, direct memory access, IOMMU and IOVA addressing, custom allocators, and memory pools, and how these mechanisms together enable high‑performance packet processing on Linux systems.
This article provides a comprehensive overview of server hardware fundamentals, covering server form factors, motherboard architecture, selection criteria, major vendors, CPU concepts and performance, NUMA, memory specifications, disk throughput and IOPS, as well as network card types and bonding modes.